University of Gadarif

BackgroundHypertension poses a significant global health threat and is associated with several complications, including erectile dysfunction (ED). Currently, there is no published data on the prevalence of ED among hypertensive patients in Sudan. Thus, this study evaluated the prevalence of ED and the associated factors among hypertensive patients in eastern Sudan.MethodsThis cross-sectional study was carried out in Gadarif, Eastern Sudan. Data on demographic characteristics, anthropometrics, blood pressure, results of the International Index of Erectile Function (IIEF-5) questionnaire, and clinical history was obtained. Multivariate binary regression analysis was used.ResultsThree hundred and twelve men with hypertension were recruited. The median (interquartile range [IQR]) age and duration of hypertension were 52.2 (46.0-59.0) years and 5.0 (3.0-7.0) years, respectively. Of the participants, 107 (34.3%) had ED. Of those with ED, 107 men were identified, with 15 (14.0%) experiencing severe ED, 10 (9.3%) experiencing moderate ED, 39 (36.4%) experiencing mild to moderate ED, and 43 (40.2%) experiencing mild ED. Multivariate binary regression revealed that increasing age (adjusted odds ratio [AOR] = 1.13 and 95% confidence interval [CI] = 1.07-1.19), increasing duration of hypertension (AOR = 1.24 and 95% CI 1.09-1.40), number of medications (AOR = 2.40 and 95% CI = 1.27-4.55), and being of low income (AOR = 2.26 and 95% CI = 1.10-4.67) were associated with ED. Education level, occupation, presence of comorbidity, tobacco use, or alcohol use were not associated with ED.ConclusionThis study reveals a significant prevalence of ED (34.3%) among men with hypertension in Eastern Sudan, with age, duration of hypertension, number of medications, and low income as key associated factors. This present study emphasizes the importance of integrated screening and management strategies to address both hypertension and ED simultaneously.

Armed conflicts pose severe challenges to healthcare workforce pipelines, with specialized surgical training being particularly vulnerable. The war in Sudan, which began in April 2023, has led to a complex humanitarian crisis, damaging health infrastructure and displacing medical professionals. The impact on postgraduate urological surgical training requires detailed assessment. A national, descriptive quantitative cross-sectional study was conducted from September to December 2024. A structured online questionnaire was distributed to the complete national cohort of urology specialty trainees (n = 40, 100

The discovery of novel materials with exceptional physical properties remains a significant challenge in the development of next-generation photovoltaic technologies. In this study, density functional theory (DFT) was employed to investigate double halide perovskites Cs2Snx_2RE2Cl6 (RE = La, Ce, Pr, Nd), where rare earth lanthanides were introduced as dopants. The electronic, optical, spin-polarized, and mechanical properties of these compounds were systematically explored. The calculated band gaps are 3.63 eV (La), 1.68 eV (Ce), 0.84 eV (Pr), and 1.01 eV (Nd), indicating a tunable optoelectronic response suitable for photovoltaic applications. The presence of both valence and conduction bands confirms their potential for efficient photo-induced charge transport. Mechanical analysis via Poisson's and Pugh's ratios confirms ductility across all compositions, supporting their integration in flexible devices. Additionally, pronounced elastic anisotropy is observed in each material. Spin-polarized density of states reveals symmetric energy distributions for spin-up and spin-down channels, indicating nonmagnetic ground states. Strong absorption in the visible region further supports the suitability of these lanthanide-doped perovskites as promising candidates for future photovoltaic applications.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is marked by a lack of communication skills in social situations and repetitive and stereotypical Behaviors. The most widespread form of diagnosing ASD among children is based on psychological screening test along with monitoring of the Behavioral pattern, especially repetitive Behaviors. Some of these Behaviors include hand-flapping, head banging and spinning which are common among ASD children. In our research, we examine abnormal Behavioral patterns that may reflect ASD through the videos of children engaged in the everyday activities in the unstructured settings. A publicly available multiclass Self-Stimulatory Behavior Dataset (SSBD) is use in classify autistic Behavior. Before training the model, the dataset is thoroughly pre-processed (region-of-interest (ROI) detection and image cropping to eliminate irrelevant background objects). Moreover, information-augmenting methods are used to reduce overfitting and increase training efficiency and generalization effectiveness. In order to obtain spatiotemporal details successfully, a number of deep learning models are tested, such as studied CNN-GRU model, 3D-CNN + LSTM, MobileNet, VGG16, and EfficientNet-B7. The findings of the experiment prove that the proposed CNN-GRU model is superior to all competing methods. The model with a k-fold cross-validation provides a steady accuracy of 0.9284 ± 0.0039-0.9294 ± 0.0038, which means that the model is robust and consistent across the folds. The effectiveness of the proposed approach is additionally justified by the comparisons with state-of-the-art methods. The results show that the systems based on the action recognition can help clinicians monitor the Behavioral trends and facilitate the quick, accurate, and effective screening of ASD. The proposed approach works effectively in predicting Behavior in real-life, uncontrolled videos and shows tremendous potential for real-world clinical implementation as a decision-support tool.

Gold (Au) nanoparticles (NPs) have been identified as essential for orchestrating an enhanced efficacy of 3D-printed scaffolds in biomedical applications. This review examines the potential of Au NPs integrated with 3D printing technologies, with a focus on their applications in cardiac, bone, and muscle tissue engineering. The integration of Au NPs into 3D printed scaffolds offers a transformative approach to enhancing scaffold performance by leveraging the physicochemical properties of Au NPs, such as their high surface-to-volume ratio, tunable optical properties, and biocompatibility. Recent advancements highlight the potential of Au NP-based 3D scaffolds in tissue regeneration, as they enhance mechanical strength, improve electrical conductivity, and facilitate controlled drug release. Additionally, these scaffolds have a positive influence on cellular activities and imaging capabilities, making them highly relevant in modern medical applications. This review explores the synergistic benefits of combining Au NPs with 3D printing, paving the way for innovative advancements in personalized medicine and therapeutic strategies. Researchers are introducing gold nanoparticles with 3D printed constructs to create advanced scaffolds that aid in repairing heart, bone, and muscle tissues. The incorporation of tiny gold particles with 3D-printed scaffolds is safe, stable, and can carry drugs and/or interact with cells. Simultaneously, they improve strength, electrical conductivity, and support cell growth. For example, in heart repair, gold nanoparticles help heart cells beat in sync, which is vital after a heart attack and these gold nanoparticles on the 3D printed scaffolds can be effective for muscle regeneration. In bone repair, they support faster and stronger growth of bone-forming cells, making recovery more effective.